Journal ArticleDOI
Multi-scale and multi-layer perceptron hybrid method for bearings fault diagnosis
TLDR
In this article , a multi-scale multi-layer perceptron (MSMLP) hybrid bearing fault diagnosis based on complementary ensemble empirical mode decomposition (CEEMD) is proposed, inspired by the successful application of deep networks in the field of computer vision.About:
This article is published in International Journal of Mechanical Sciences.The article was published on 2022-08-01. It has received 10 citations till now. The article focuses on the topics: Hilbert–Huang transform & Perceptron.read more
Citations
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Journal ArticleDOI
Improving Building Occupant Comfort through a Digital Twin Approach: A Bayesian Network Model and Predictive Maintenance Method
TL;DR: In this paper , a Digital Twin approach is proposed to integrate building information modeling (BIM) with real-time sensor data, occupant feedback, and a probabilistic model of occupant comfort to detect and predict HVAC issues that may impact comfort.
Journal ArticleDOI
A Probabilistic Bayesian Parallel Deep Learning Framework for Wind Turbine Bearing Fault Diagnosis
TL;DR: Experimental results show that the BayesianPDL framework has unique advantages in the fault diagnosis of wind turbine bearings and the confidence in diagnostic results is higher than other comparison methods.
Journal ArticleDOI
Improved MLP Energy Meter Fault Diagnosis Method Based on DBN
TL;DR: Wang et al. as discussed by the authors proposed a DBN-MLP fusion neural network method for multi-dimensional analysis and fault-type diagnosis of smart energy meter fault data, which can effectively reduce the number of training iterations and improve the accuracy of diagnosis.
Proceedings ArticleDOI
Intelligent Diagnosis of Engine Failure in Air Vehicles Using the ALFA Dataset
TL;DR: In this article , a machine learning algorithm based on Multi-Layer Perceptron, Support Vector Machine, Gradient Boosting, and Random Foresting was proposed to detect engine failures in electric Vertical Take-Off and Landing aircraft (eVTOLs).
Journal ArticleDOI
Fault diagnosis of rotating machinery via multi-structure fusion discriminative projection
TL;DR: Wang et al. as discussed by the authors proposed a rotating machinery fault diagnosis method based on multi-structure fusion discriminative projection (MFDP), which constructed intraclass and interclass hypergraph structures with multivariate relationships, revealing the higher-order association information among multiple samples.
References
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Journal ArticleDOI
Practical method for determining the minimum embedding dimension of a scalar time series
TL;DR: A practical method to determine the minimum embedding dimension from a scalar time series that has the following advantages: does not contain any subjective parameters except for the time-delay for the embedding.
Journal ArticleDOI
Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study
Wade A. Smith,Robert B. Randall +1 more
TL;DR: Though intended primarily as a benchmark to aid in testing new diagnostic algorithms, it is also hoped that much of the discussion will have broader applicability to other bearing diagnostics cases.
Journal ArticleDOI
Nonlinear dynamics, delay times, and embedding windows
TL;DR: In this article, the authors proposed a simpler method for estimating the delay time of a nonlinear time series using the correlation integral, which is known as the C-C method.
Book ChapterDOI
Time series classification using multi-channels deep convolutional neural networks
TL;DR: A novel deep learning framework for multivariate time series classification is proposed that is not only more efficient than the state of the art but also competitive in accuracy and demonstrates that feature learning is worth to investigate for time series Classification.
Journal ArticleDOI
Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert-Huang transform
V.K. Rai,Amiya R Mohanty +1 more
TL;DR: In this paper, a Hilbert-Huang Transform (HHT) based time domain approach for bearing vibration signature analysis is proposed for bearing bearing vibration analysis and its efficiency is evaluated.